Companies want to train their own large models on their own data, but the current industry standard of training on a random sample of data is inefficient and can harm model quality. DatologyAI aims to translate research into tools that enable enterprise customers to identify the right data for training, resulting in better models for cheaper.
Requirements
- Strong programming skills in Python, Go, or C++
- Familiar with Linux systems, Docker, Kubernetes, or similar technologies
- Curious about cloud computing (AWS, Azure, or GCP) and large-scale distributed systems
Responsibilities
- Build and improve internal tools that accelerate developer productivity and system reliability
- Design and prototype components of DatologyAI’s distributed training and data infrastructure
- Contribute to automation, deployment, and observability systems across multi-cloud and on-prem environments
- Collaborate with engineers and researchers to bring new ML infrastructure capabilities to production
- Participate in code reviews, technical discussions, and learn best practices for scalable infrastructure development
Other
- Pursuing a BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field
- Excited to learn how infrastructure enables ML research and model deployment at scale
- Collaborative, detail-oriented, and eager to take on complex technical problems
- This role is based in Redwood City, CA. We are in office 4 days a week.
- If you are not currently located in the Bay Area, we provide a relocation stipendto help cover travel and living expenses during your three months on-site.
